Overview

Brought to you by YData

Dataset statistics

Number of variables20
Number of observations13525
Missing cells7144
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.6 MiB
Average record size in memory1.6 KiB

Variable types

Numeric13
Text6
URL1

Alerts

1_star_ratings is highly overall correlated with 2_star_ratings and 6 other fieldsHigh correlation
2_star_ratings is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
3_star_ratings is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
4_star_ratings is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
5_star_ratings is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
original_publication_year is highly overall correlated with work_idHigh correlation
ratings_count is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
reviews_count is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
text_reviews_count is highly overall correlated with 1_star_ratings and 6 other fieldsHigh correlation
work_id is highly overall correlated with original_publication_yearHigh correlation
isbn has 2051 (15.2%) missing values Missing
isbn13 has 1661 (12.3%) missing values Missing
num_pages has 730 (5.4%) missing values Missing
description has 169 (1.2%) missing values Missing
similar_books has 2515 (18.6%) missing values Missing
original_publication_year is highly skewed (γ1 = -30.80063832) Skewed
1_star_ratings is highly skewed (γ1 = 44.51194236) Skewed
work_id has unique values Unique

Reproduction

Analysis started2025-08-02 14:13:02.751882
Analysis finished2025-08-02 14:13:31.932045
Duration29.18 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

work_id
Real number (ℝ)

High correlation  Unique 

Distinct13525
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18436259
Minimum104
Maximum57717521
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:32.045479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile284949
Q12953328
median15992791
Q325878877
95-th percentile48262060
Maximum57717521
Range57717417
Interquartile range (IQR)22925549

Descriptive statistics

Standard deviation16258712
Coefficient of variation (CV)0.88188785
Kurtosis-0.78358409
Mean18436259
Median Absolute Deviation (MAD)12431125
Skewness0.66069545
Sum2.493504 × 1011
Variance2.6434573 × 1014
MonotonicityNot monotonic
2025-08-02T14:13:32.207777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51402505 1
 
< 0.1%
2919130 1
 
< 0.1%
52087333 1
 
< 0.1%
1649583 1
 
< 0.1%
688299 1
 
< 0.1%
56016392 1
 
< 0.1%
56407508 1
 
< 0.1%
49707266 1
 
< 0.1%
50867364 1
 
< 0.1%
55118452 1
 
< 0.1%
Other values (13515) 13515
99.9%
ValueCountFrequency (%)
104 1
< 0.1%
114 1
< 0.1%
115 1
< 0.1%
423 1
< 0.1%
434 1
< 0.1%
505 1
< 0.1%
696 1
< 0.1%
797 1
< 0.1%
817 1
< 0.1%
860 1
< 0.1%
ValueCountFrequency (%)
57717521 1
< 0.1%
57646853 1
< 0.1%
57438069 1
< 0.1%
57414860 1
< 0.1%
57407230 1
< 0.1%
57400201 1
< 0.1%
57104739 1
< 0.1%
56947505 1
< 0.1%
56847346 1
< 0.1%
56825332 1
< 0.1%

isbn
Text

Missing 

Distinct11474
Distinct (%)100.0%
Missing2051
Missing (%)15.2%
Memory size815.0 KiB
2025-08-02T14:13:32.546867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9998257
Min length9

Characters and Unicode

Total characters114738
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11474 ?
Unique (%)100.0%

Sample

1st row1416534601
2nd row1416505520
3rd row0060541830
4th row0451528824
5th row0425210138
ValueCountFrequency (%)
0609807919 1
 
< 0.1%
1627985549 1
 
< 0.1%
0451459245 1
 
< 0.1%
1569319960 1
 
< 0.1%
1841493147 1
 
< 0.1%
0930289447 1
 
< 0.1%
0060567236 1
 
< 0.1%
0590554107 1
 
< 0.1%
1101885939 1
 
< 0.1%
0553296981 1
 
< 0.1%
Other values (11464) 11464
99.9%
2025-08-02T14:13:33.011860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18783
16.4%
1 14458
12.6%
4 11999
10.5%
5 11542
10.1%
3 10801
9.4%
6 10328
9.0%
2 10293
9.0%
7 9133
8.0%
9 8336
7.3%
8 8104
7.1%
Other values (2) 961
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 114738
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 18783
16.4%
1 14458
12.6%
4 11999
10.5%
5 11542
10.1%
3 10801
9.4%
6 10328
9.0%
2 10293
9.0%
7 9133
8.0%
9 8336
7.3%
8 8104
7.1%
Other values (2) 961
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 114738
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 18783
16.4%
1 14458
12.6%
4 11999
10.5%
5 11542
10.1%
3 10801
9.4%
6 10328
9.0%
2 10293
9.0%
7 9133
8.0%
9 8336
7.3%
8 8104
7.1%
Other values (2) 961
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 114738
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 18783
16.4%
1 14458
12.6%
4 11999
10.5%
5 11542
10.1%
3 10801
9.4%
6 10328
9.0%
2 10293
9.0%
7 9133
8.0%
9 8336
7.3%
8 8104
7.1%
Other values (2) 961
 
0.8%

isbn13
Real number (ℝ)

Missing 

Distinct11864
Distinct (%)100.0%
Missing1661
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean9.7471654 × 1012
Minimum9.7814525 × 109
Maximum9.8765432 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:33.164815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9.7814525 × 109
5-th percentile9.7800616 × 1012
Q19.7803455 × 1012
median9.7806156 × 1012
Q39.7814215 × 1012
95-th percentile9.7816348 × 1012
Maximum9.8765432 × 1012
Range9.8667618 × 1012
Interquartile range (IQR)1.0759588 × 109

Descriptive statistics

Standard deviation4.9683873 × 1011
Coefficient of variation (CV)0.050972638
Kurtosis225.61419
Mean9.7471654 × 1012
Median Absolute Deviation (MAD)3.7390713 × 108
Skewness-14.941611
Sum1.1564037 × 1017
Variance2.4684873 × 1023
MonotonicityNot monotonic
2025-08-02T14:13:33.317770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.780062333 × 10121
 
< 0.1%
9.781633752 × 10121
 
< 0.1%
9.78144243 × 10121
 
< 0.1%
9.780062281 × 10121
 
< 0.1%
9.780373211 × 10121
 
< 0.1%
9.78125004 × 10121
 
< 0.1%
9.781402287 × 10121
 
< 0.1%
9.780345543 × 10121
 
< 0.1%
9.780316278 × 10121
 
< 0.1%
9.781451685 × 10121
 
< 0.1%
Other values (11854) 11854
87.6%
(Missing) 1661
 
12.3%
ValueCountFrequency (%)
9781452497 1
< 0.1%
9781623420 1
< 0.1%
9.789380659 × 10101
< 0.1%
9.780061895 × 10111
< 0.1%
9.780425242 × 10111
< 0.1%
9.781599905 × 10111
< 0.1%
1.230000001 × 10121
< 0.1%
1.230000005 × 10121
< 0.1%
1.23000001 × 10121
< 0.1%
1.230000106 × 10121
< 0.1%
ValueCountFrequency (%)
9.876543211 × 10121
< 0.1%
9.790007672 × 10121
< 0.1%
9.789993912 × 10121
< 0.1%
9.789871144 × 10121
< 0.1%
9.789812695 × 10121
< 0.1%
9.789792772 × 10121
< 0.1%
9.789792767 × 10121
< 0.1%
9.789715424 × 10121
< 0.1%
9.789715086 × 10121
< 0.1%
9.789626344 × 10121
< 0.1%
Distinct13029
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size1003.2 KiB
2025-08-02T14:13:33.681852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length223
Median length122
Mean length18.945952
Min length1

Characters and Unicode

Total characters256244
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12641 ?
Unique (%)93.5%

Sample

1st rowNocturnes
2nd rowDraw Play
3rd rowCitizen of the Galaxy
4th rowCongo
5th rowAnne of Green Gables
ValueCountFrequency (%)
the 4821
 
10.6%
of 1932
 
4.2%
a 984
 
2.2%
and 672
 
1.5%
in 504
 
1.1%
1 415
 
0.9%
to 385
 
0.8%
you 245
 
0.5%
239
 
0.5%
2 221
 
0.5%
Other values (9871) 35201
77.2%
2025-08-02T14:13:34.404626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32203
 
12.6%
e 26850
 
10.5%
o 14931
 
5.8%
a 14558
 
5.7%
n 13610
 
5.3%
i 13480
 
5.3%
r 13473
 
5.3%
t 12214
 
4.8%
s 10432
 
4.1%
h 9846
 
3.8%
Other values (74) 94647
36.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 256244
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
32203
 
12.6%
e 26850
 
10.5%
o 14931
 
5.8%
a 14558
 
5.7%
n 13610
 
5.3%
i 13480
 
5.3%
r 13473
 
5.3%
t 12214
 
4.8%
s 10432
 
4.1%
h 9846
 
3.8%
Other values (74) 94647
36.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 256244
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
32203
 
12.6%
e 26850
 
10.5%
o 14931
 
5.8%
a 14558
 
5.7%
n 13610
 
5.3%
i 13480
 
5.3%
r 13473
 
5.3%
t 12214
 
4.8%
s 10432
 
4.1%
h 9846
 
3.8%
Other values (74) 94647
36.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 256244
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
32203
 
12.6%
e 26850
 
10.5%
o 14931
 
5.8%
a 14558
 
5.7%
n 13610
 
5.3%
i 13480
 
5.3%
r 13473
 
5.3%
t 12214
 
4.8%
s 10432
 
4.1%
h 9846
 
3.8%
Other values (74) 94647
36.9%

author
Text

Distinct5554
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Memory size929.5 KiB
2025-08-02T14:13:34.917134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length35
Median length28
Mean length13.364658
Min length3

Characters and Unicode

Total characters180757
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3340 ?
Unique (%)24.7%

Sample

1st rowJohn Connolly
2nd rowTia Lewis
3rd rowRobert A. Heinlein
4th rowMichael Crichton
5th rowL.M. Montgomery
ValueCountFrequency (%)
james 176
 
0.6%
jennifer 172
 
0.6%
elizabeth 163
 
0.6%
sarah 152
 
0.5%
john 149
 
0.5%
robert 134
 
0.5%
scott 122
 
0.4%
lisa 118
 
0.4%
rachel 112
 
0.4%
lauren 109
 
0.4%
Other values (5809) 27133
95.1%
2025-08-02T14:13:35.641153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 17341
 
9.6%
a 17011
 
9.4%
15463
 
8.6%
n 13482
 
7.5%
r 11934
 
6.6%
i 11193
 
6.2%
l 8643
 
4.8%
o 8557
 
4.7%
t 6516
 
3.6%
s 6500
 
3.6%
Other values (48) 64117
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 180757
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 17341
 
9.6%
a 17011
 
9.4%
15463
 
8.6%
n 13482
 
7.5%
r 11934
 
6.6%
i 11193
 
6.2%
l 8643
 
4.8%
o 8557
 
4.7%
t 6516
 
3.6%
s 6500
 
3.6%
Other values (48) 64117
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 180757
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 17341
 
9.6%
a 17011
 
9.4%
15463
 
8.6%
n 13482
 
7.5%
r 11934
 
6.6%
i 11193
 
6.2%
l 8643
 
4.8%
o 8557
 
4.7%
t 6516
 
3.6%
s 6500
 
3.6%
Other values (48) 64117
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 180757
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 17341
 
9.6%
a 17011
 
9.4%
15463
 
8.6%
n 13482
 
7.5%
r 11934
 
6.6%
i 11193
 
6.2%
l 8643
 
4.8%
o 8557
 
4.7%
t 6516
 
3.6%
s 6500
 
3.6%
Other values (48) 64117
35.5%

original_publication_year
Real number (ℝ)

High correlation  Skewed 

Distinct226
Distinct (%)1.7%
Missing18
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2003.0801
Minimum-500
Maximum2021
Zeros0
Zeros (%)0.0%
Negative6
Negative (%)< 0.1%
Memory size105.8 KiB
2025-08-02T14:13:35.843210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-500
5-th percentile1967
Q12006
median2011
Q32014
95-th percentile2016
Maximum2021
Range2521
Interquartile range (IQR)8

Descriptive statistics

Standard deviation59.253869
Coefficient of variation (CV)0.029581378
Kurtosis1186.7179
Mean2003.0801
Median Absolute Deviation (MAD)3
Skewness-30.800638
Sum27055603
Variance3511.021
MonotonicityNot monotonic
2025-08-02T14:13:36.075452image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2013 1393
 
10.3%
2012 1324
 
9.8%
2014 1227
 
9.1%
2015 1156
 
8.5%
2011 1135
 
8.4%
2016 971
 
7.2%
2010 770
 
5.7%
2009 687
 
5.1%
2017 526
 
3.9%
2008 484
 
3.6%
Other values (216) 3834
28.3%
ValueCountFrequency (%)
-500 1
< 0.1%
-441 1
< 0.1%
-430 1
< 0.1%
-405 1
< 0.1%
-390 1
< 0.1%
-19 1
< 0.1%
800 1
< 0.1%
975 1
< 0.1%
1008 1
< 0.1%
1516 1
< 0.1%
ValueCountFrequency (%)
2021 1
 
< 0.1%
2018 7
 
0.1%
2017 526
 
3.9%
2016 971
7.2%
2015 1156
8.5%
2014 1227
9.1%
2013 1393
10.3%
2012 1324
9.8%
2011 1135
8.4%
2010 770
5.7%

num_pages
Real number (ℝ)

Missing 

Distinct827
Distinct (%)6.5%
Missing730
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean335.28191
Minimum1
Maximum2201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:36.303879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile128
Q1260
median334
Q3391
95-th percentile551.3
Maximum2201
Range2200
Interquartile range (IQR)131

Descriptive statistics

Standard deviation137.88656
Coefficient of variation (CV)0.41125559
Kurtosis9.2716701
Mean335.28191
Median Absolute Deviation (MAD)66
Skewness1.5437331
Sum4289932
Variance19012.703
MonotonicityNot monotonic
2025-08-02T14:13:36.502731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
384 300
 
2.2%
320 293
 
2.2%
352 283
 
2.1%
336 259
 
1.9%
368 234
 
1.7%
304 214
 
1.6%
400 188
 
1.4%
288 181
 
1.3%
416 150
 
1.1%
256 132
 
1.0%
Other values (817) 10561
78.1%
(Missing) 730
 
5.4%
ValueCountFrequency (%)
1 1
 
< 0.1%
3 2
 
< 0.1%
4 6
< 0.1%
5 1
 
< 0.1%
6 4
< 0.1%
8 3
< 0.1%
9 1
 
< 0.1%
10 3
< 0.1%
11 1
 
< 0.1%
13 2
 
< 0.1%
ValueCountFrequency (%)
2201 1
< 0.1%
1474 1
< 0.1%
1463 1
< 0.1%
1443 1
< 0.1%
1427 1
< 0.1%
1392 2
< 0.1%
1280 2
< 0.1%
1276 1
< 0.1%
1273 1
< 0.1%
1243 1
< 0.1%

description
Text

Missing 

Distinct13352
Distinct (%)> 99.9%
Missing169
Missing (%)1.2%
Memory size12.3 MiB
2025-08-02T14:13:36.915724image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5483
Median length1610
Mean length908.43104
Min length21

Characters and Unicode

Total characters12133005
Distinct characters95
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13349 ?
Unique (%)99.9%

Sample

1st rowJake: I can't believe my coach assigned me a tutor. I'm all that on the field and between the sheets -- who cares about my stupid grades? But Claire doesn't treat me like I'm dumb. When we're not busy fighting, she actually encourages me. And with those sexy curves of hers, I know just how to thank her. Claire: I hate football players, but I need the money. Jake is just as cocky and arrogant as the worst of them ... but his touch sets me on fire. I have to believe he's different, that he won't use me and break my heart. Because I can't stop wanting him. I just hope I survive the ride.
2nd rowIn a distant galaxy, the atrocity of slavery was alive and well, and young Thorby was just another orphaned boy sold at auction. But his new owner, Baslim, is not the disabled beggar he appears to be: adopting Thorby as his son, he fights relentlessly as an abolitionist spy. When the authorities close in on Baslim, Thorby must ride with the Free Traders a league of merchant princes throughout the many worlds of a hostile galaxy, finding the courage to live by his wits and fight his way from society's lowest rung. But Thorby's destiny will be forever changed when he discovers the truth about his own identity...
3rd rowDeep in the African rain forest, near the legendary ruins of the Lost City of Zinj, an expedition of eight American geologists is mysteriously and brutally killed in a matter of minutes. Ten thousand miles away, Karen Ross, the Congo Project Supervisor, watches a gruesome video transmission of the aftermath: a camp destroyed, tents crushed and torn, equipment scattered in the mud alongside dead bodies -- all motionless except for one moving image -- a grainy, dark, man-shaped blur. In San Francisco, primatologist Peter Elliot works with Amy, a gorilla with an extraordinary vocabulary of 620 "signs," the most ever learned by a primate, and she likes to fingerpaint. But recently, her behavior has been erratic and her drawings match, with stunning accuracy, the brittle pages of a Portuguese print dating back to 1642 . . . a drawing of an ancient lost city. A new expedition -- along with Amy -- is sent into the Congo where they enter a secret world, and the only way out may be through a horrifying death . . .
4th rowEveryone's favorite redhead, the spunky Anne Shirley, begins her adventures at Green Gables, a farm outside Avonlea, Prince Edward Island. When the freckled girl realizes that the elderly Cuthberts wanted to adopt a boy instead, she begins to try to win them and, consequently, the reader, over.
5th rowFrom the USA Today bestselling author, a vampire-meets-girl story set in the city that never sleeps-except during daylight. He's a bloodsucking freak of nature. But, unlike other politicians, Ethan Carrick is actually a nice guy. Not to mention a very hot, wealthy, casino-owning vampire. It's an election year for vampires, which means he'll first have to escape his opponent's hit men. Then he'll have to find a suitable First Lady, preferably here in Vegas. Brittany Baldizzi fits the bill. She's smart, pretty- and sweeter than a glass of diabetic O-Negative. But her protective sister Alexis steps in with a message for Ethan: Bite me. It's then that he realizes it's the sexy, no-nonsense Alexis who raises his stake. And as much as she denies it, Alexis wouldn't mind a romp in the coffin with him. But can a mere mortal, even one who risks her life for him, make a centuries-old, womanizing vampire feel something entirely new?
ValueCountFrequency (%)
the 110472
 
5.3%
and 65741
 
3.2%
a 61873
 
3.0%
to 59364
 
2.9%
of 56089
 
2.7%
her 34488
 
1.7%
in 32877
 
1.6%
is 30042
 
1.4%
his 19750
 
1.0%
she 18685
 
0.9%
Other values (82858) 1582810
76.4%
2025-08-02T14:13:37.923918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2026130
16.7%
e 1209415
 
10.0%
t 803171
 
6.6%
a 757057
 
6.2%
n 699910
 
5.8%
o 681062
 
5.6%
i 661944
 
5.5%
s 648623
 
5.3%
r 615884
 
5.1%
h 537556
 
4.4%
Other values (85) 3492253
28.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12133005
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2026130
16.7%
e 1209415
 
10.0%
t 803171
 
6.6%
a 757057
 
6.2%
n 699910
 
5.8%
o 681062
 
5.6%
i 661944
 
5.5%
s 648623
 
5.3%
r 615884
 
5.1%
h 537556
 
4.4%
Other values (85) 3492253
28.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12133005
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2026130
16.7%
e 1209415
 
10.0%
t 803171
 
6.6%
a 757057
 
6.2%
n 699910
 
5.8%
o 681062
 
5.6%
i 661944
 
5.5%
s 648623
 
5.3%
r 615884
 
5.1%
h 537556
 
4.4%
Other values (85) 3492253
28.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12133005
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2026130
16.7%
e 1209415
 
10.0%
t 803171
 
6.6%
a 757057
 
6.2%
n 699910
 
5.8%
o 681062
 
5.6%
i 661944
 
5.5%
s 648623
 
5.3%
r 615884
 
5.1%
h 537556
 
4.4%
Other values (85) 3492253
28.8%

genres
Text

Distinct1712
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
2025-08-02T14:13:38.089412image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length237
Median length129
Mean length57.881183
Min length7

Characters and Unicode

Total characters782843
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique917 ?
Unique (%)6.8%

Sample

1st rowfiction, fantasy, paranormal, mystery, thriller, crime, young-adult
2nd rowromance, fiction
3rd rowfiction, young-adult, fantasy, paranormal, children
4th rowfiction, mystery, thriller, crime, fantasy, paranormal
5th rowfiction, young-adult, children, history, historical fiction, biography, romance
ValueCountFrequency (%)
fiction 17141
20.6%
romance 9255
11.1%
fantasy 7407
8.9%
paranormal 7407
8.9%
crime 6607
 
7.9%
mystery 6607
 
7.9%
thriller 6607
 
7.9%
young-adult 6450
 
7.7%
history 3954
 
4.7%
historical 3954
 
4.7%
Other values (6) 7956
9.5%
2025-08-02T14:13:38.417167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69820
 
8.9%
i 67733
 
8.7%
, 65866
 
8.4%
r 64799
 
8.3%
a 61609
 
7.9%
o 54460
 
7.0%
t 52903
 
6.8%
n 50760
 
6.5%
c 41738
 
5.3%
y 35161
 
4.5%
Other values (12) 217994
27.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 782843
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
69820
 
8.9%
i 67733
 
8.7%
, 65866
 
8.4%
r 64799
 
8.3%
a 61609
 
7.9%
o 54460
 
7.0%
t 52903
 
6.8%
n 50760
 
6.5%
c 41738
 
5.3%
y 35161
 
4.5%
Other values (12) 217994
27.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 782843
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
69820
 
8.9%
i 67733
 
8.7%
, 65866
 
8.4%
r 64799
 
8.3%
a 61609
 
7.9%
o 54460
 
7.0%
t 52903
 
6.8%
n 50760
 
6.5%
c 41738
 
5.3%
y 35161
 
4.5%
Other values (12) 217994
27.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 782843
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
69820
 
8.9%
i 67733
 
8.7%
, 65866
 
8.4%
r 64799
 
8.3%
a 61609
 
7.9%
o 54460
 
7.0%
t 52903
 
6.8%
n 50760
 
6.5%
c 41738
 
5.3%
y 35161
 
4.5%
Other values (12) 217994
27.8%
Distinct10901
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
https://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png
2625 
https://images.gr-assets.com/books/1405301042m/19286545.jpg
 
1
https://images.gr-assets.com/books/1428633690m/16007911.jpg
 
1
https://images.gr-assets.com/books/1358394937m/13532153.jpg
 
1
https://images.gr-assets.com/books/1331339352m/12083233.jpg
 
1
Other values (10896)
10896 
ValueCountFrequency (%)
https://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png 2625
 
19.4%
https://images.gr-assets.com/books/1405301042m/19286545.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1428633690m/16007911.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1358394937m/13532153.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1331339352m/12083233.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1353173297m/13547180.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1355090370m/13366929.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1320604137m/11559200.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1332688725m/12326644.jpg 1
 
< 0.1%
https://images.gr-assets.com/books/1397879349m/12873027.jpg 1
 
< 0.1%
Other values (10891) 10891
80.5%
ValueCountFrequency (%)
https 13525
100.0%
ValueCountFrequency (%)
images.gr-assets.com 10900
80.6%
s.gr-assets.com 2625
 
19.4%
ValueCountFrequency (%)
/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png 2625
 
19.4%
/books/1405301042m/19286545.jpg 1
 
< 0.1%
/books/1428633690m/16007911.jpg 1
 
< 0.1%
/books/1358394937m/13532153.jpg 1
 
< 0.1%
/books/1331339352m/12083233.jpg 1
 
< 0.1%
/books/1353173297m/13547180.jpg 1
 
< 0.1%
/books/1355090370m/13366929.jpg 1
 
< 0.1%
/books/1320604137m/11559200.jpg 1
 
< 0.1%
/books/1332688725m/12326644.jpg 1
 
< 0.1%
/books/1397879349m/12873027.jpg 1
 
< 0.1%
Other values (10891) 10891
80.5%
ValueCountFrequency (%)
13525
100.0%
ValueCountFrequency (%)
13525
100.0%

reviews_count
Real number (ℝ)

High correlation 

Distinct11948
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61440.947
Minimum107
Maximum6057595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:38.544122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum107
5-th percentile2013
Q16804
median16588
Q344017
95-th percentile224199.6
Maximum6057595
Range6057488
Interquartile range (IQR)37213

Descriptive statistics

Standard deviation203063.38
Coefficient of variation (CV)3.3050171
Kurtosis214.05525
Mean61440.947
Median Absolute Deviation (MAD)12293
Skewness11.923839
Sum8.3098881 × 108
Variance4.1234738 × 1010
MonotonicityNot monotonic
2025-08-02T14:13:38.701355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4295 5
 
< 0.1%
5065 4
 
< 0.1%
4113 4
 
< 0.1%
2584 4
 
< 0.1%
935 4
 
< 0.1%
5539 4
 
< 0.1%
3281 4
 
< 0.1%
1984 4
 
< 0.1%
6253 4
 
< 0.1%
5321 4
 
< 0.1%
Other values (11938) 13484
99.7%
ValueCountFrequency (%)
107 1
< 0.1%
142 1
< 0.1%
151 1
< 0.1%
186 1
< 0.1%
190 1
< 0.1%
226 1
< 0.1%
244 1
< 0.1%
245 1
< 0.1%
298 1
< 0.1%
309 1
< 0.1%
ValueCountFrequency (%)
6057595 1
< 0.1%
5801988 1
< 0.1%
4637197 1
< 0.1%
4557554 1
< 0.1%
3745299 1
< 0.1%
3614315 1
< 0.1%
3206476 1
< 0.1%
3103888 1
< 0.1%
3089773 1
< 0.1%
2942483 1
< 0.1%

text_reviews_count
Real number (ℝ)

High correlation 

Distinct4210
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2036.7291
Minimum18
Maximum156575
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:38.838961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile113
Q1286
median664
Q31709
95-th percentile7876.6
Maximum156575
Range156557
Interquartile range (IQR)1423

Descriptive statistics

Standard deviation5429.4744
Coefficient of variation (CV)2.6657813
Kurtosis174.30901
Mean2036.7291
Median Absolute Deviation (MAD)467
Skewness10.415106
Sum27546761
Variance29479193
MonotonicityNot monotonic
2025-08-02T14:13:39.000477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207 31
 
0.2%
130 28
 
0.2%
160 27
 
0.2%
178 25
 
0.2%
177 25
 
0.2%
227 23
 
0.2%
120 23
 
0.2%
121 23
 
0.2%
118 23
 
0.2%
309 23
 
0.2%
Other values (4200) 13274
98.1%
ValueCountFrequency (%)
18 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
28 1
< 0.1%
30 1
< 0.1%
34 2
< 0.1%
35 1
< 0.1%
36 1
< 0.1%
37 1
< 0.1%
38 1
< 0.1%
ValueCountFrequency (%)
156575 1
< 0.1%
142351 1
< 0.1%
122540 1
< 0.1%
101874 1
< 0.1%
96736 1
< 0.1%
95698 1
< 0.1%
95618 1
< 0.1%
95084 1
< 0.1%
89071 1
< 0.1%
78753 1
< 0.1%

5_star_ratings
Real number (ℝ)

High correlation 

Distinct7732
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14398.016
Minimum5
Maximum3131920
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:39.161594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile160
Q1759
median2343
Q37925
95-th percentile48279.6
Maximum3131920
Range3131915
Interquartile range (IQR)7166

Descriptive statistics

Standard deviation70546.225
Coefficient of variation (CV)4.8997186
Kurtosis585.833
Mean14398.016
Median Absolute Deviation (MAD)1967
Skewness19.419852
Sum1.9473316 × 108
Variance4.9767698 × 109
MonotonicityNot monotonic
2025-08-02T14:13:39.312250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 16
 
0.1%
393 13
 
0.1%
191 13
 
0.1%
366 12
 
0.1%
139 12
 
0.1%
204 12
 
0.1%
335 11
 
0.1%
306 11
 
0.1%
536 11
 
0.1%
158 11
 
0.1%
Other values (7722) 13403
99.1%
ValueCountFrequency (%)
5 1
< 0.1%
7 1
< 0.1%
10 1
< 0.1%
11 2
< 0.1%
12 2
< 0.1%
15 1
< 0.1%
18 2
< 0.1%
19 2
< 0.1%
21 1
< 0.1%
22 2
< 0.1%
ValueCountFrequency (%)
3131920 1
< 0.1%
2768578 1
< 0.1%
1748429 1
< 0.1%
1383583 1
< 0.1%
1351908 1
< 0.1%
1351479 1
< 0.1%
1303937 1
< 0.1%
1227707 1
< 0.1%
1190925 1
< 0.1%
1183534 1
< 0.1%

4_star_ratings
Real number (ℝ)

High correlation 

Distinct7927
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12172.178
Minimum4
Maximum1519190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:39.457397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile234
Q1947
median2650
Q37854
95-th percentile43890.8
Maximum1519190
Range1519186
Interquartile range (IQR)6907

Descriptive statistics

Standard deviation45514.637
Coefficient of variation (CV)3.7392354
Kurtosis240.64186
Mean12172.178
Median Absolute Deviation (MAD)2113
Skewness12.760359
Sum1.646287 × 108
Variance2.0715822 × 109
MonotonicityNot monotonic
2025-08-02T14:13:39.624999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
960 10
 
0.1%
541 10
 
0.1%
181 10
 
0.1%
149 9
 
0.1%
579 9
 
0.1%
544 9
 
0.1%
2243 9
 
0.1%
562 9
 
0.1%
281 9
 
0.1%
676 8
 
0.1%
Other values (7917) 13433
99.3%
ValueCountFrequency (%)
4 1
< 0.1%
9 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 2
< 0.1%
17 1
< 0.1%
20 1
< 0.1%
21 2
< 0.1%
22 1
< 0.1%
ValueCountFrequency (%)
1519190 1
< 0.1%
1190752 1
< 0.1%
1019990 1
< 0.1%
961196 1
< 0.1%
891629 1
< 0.1%
731422 1
< 0.1%
723931 1
< 0.1%
716202 1
< 0.1%
713662 1
< 0.1%
696715 1
< 0.1%

3_star_ratings
Real number (ℝ)

High correlation 

Distinct6494
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6903.0234
Minimum4
Maximum808753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:39.782389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile156.2
Q1596
median1576
Q34463
95-th percentile25467.2
Maximum808753
Range808749
Interquartile range (IQR)3867

Descriptive statistics

Standard deviation25035.567
Coefficient of variation (CV)3.6267538
Kurtosis227.10269
Mean6903.0234
Median Absolute Deviation (MAD)1230
Skewness12.423992
Sum93363392
Variance6.267796 × 108
MonotonicityNot monotonic
2025-08-02T14:13:39.934506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
232 18
 
0.1%
242 14
 
0.1%
194 14
 
0.1%
327 13
 
0.1%
299 13
 
0.1%
445 12
 
0.1%
165 12
 
0.1%
301 12
 
0.1%
337 12
 
0.1%
255 12
 
0.1%
Other values (6484) 13393
99.0%
ValueCountFrequency (%)
4 1
 
< 0.1%
5 1
 
< 0.1%
6 2
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
13 4
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
808753 1
< 0.1%
620901 1
< 0.1%
577431 1
< 0.1%
466550 1
< 0.1%
466450 1
< 0.1%
463795 1
< 0.1%
459893 1
< 0.1%
453524 1
< 0.1%
441197 1
< 0.1%
433516 1
< 0.1%

2_star_ratings
Real number (ℝ)

High correlation 

Distinct3589
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1914.2174
Minimum0
Maximum444888
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:40.095350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36
Q1146
median383
Q31100
95-th percentile6737.2
Maximum444888
Range444888
Interquartile range (IQR)954

Descriptive statistics

Standard deviation8474.2319
Coefficient of variation (CV)4.4269954
Kurtosis690.26317
Mean1914.2174
Median Absolute Deviation (MAD)299
Skewness19.651067
Sum25889791
Variance71812606
MonotonicityNot monotonic
2025-08-02T14:13:40.246924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 40
 
0.3%
61 39
 
0.3%
54 33
 
0.2%
62 33
 
0.2%
50 33
 
0.2%
56 33
 
0.2%
65 33
 
0.2%
23 33
 
0.2%
48 33
 
0.2%
57 32
 
0.2%
Other values (3579) 13183
97.5%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 2
 
< 0.1%
2 3
 
< 0.1%
3 5
 
< 0.1%
4 14
0.1%
5 7
 
0.1%
6 8
0.1%
7 14
0.1%
8 13
0.1%
9 19
0.1%
ValueCountFrequency (%)
444888 1
< 0.1%
201694 1
< 0.1%
188876 1
< 0.1%
162978 1
< 0.1%
162442 1
< 0.1%
155569 1
< 0.1%
153935 1
< 0.1%
151342 1
< 0.1%
148072 1
< 0.1%
137191 1
< 0.1%

1_star_ratings
Real number (ℝ)

High correlation  Skewed 

Distinct2262
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean832.53575
Minimum0
Maximum463808
Zeros17
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:40.390560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q144
median123
Q3369
95-th percentile2594.2
Maximum463808
Range463808
Interquartile range (IQR)325

Descriptive statistics

Standard deviation5781.346
Coefficient of variation (CV)6.9442615
Kurtosis3154.8647
Mean832.53575
Median Absolute Deviation (MAD)98
Skewness44.511942
Sum11260046
Variance33423961
MonotonicityNot monotonic
2025-08-02T14:13:40.543820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 102
 
0.8%
18 102
 
0.8%
17 96
 
0.7%
12 94
 
0.7%
13 94
 
0.7%
6 91
 
0.7%
7 90
 
0.7%
22 87
 
0.6%
15 87
 
0.6%
19 86
 
0.6%
Other values (2252) 12596
93.1%
ValueCountFrequency (%)
0 17
 
0.1%
1 41
0.3%
2 43
0.3%
3 73
0.5%
4 66
0.5%
5 62
0.5%
6 91
0.7%
7 90
0.7%
8 82
0.6%
9 85
0.6%
ValueCountFrequency (%)
463808 1
< 0.1%
167301 1
< 0.1%
111547 1
< 0.1%
103900 1
< 0.1%
101755 1
< 0.1%
101423 1
< 0.1%
94263 1
< 0.1%
88655 1
< 0.1%
83914 1
< 0.1%
79366 1
< 0.1%

ratings_count
Real number (ℝ)

High correlation 

Distinct10542
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36219.97
Minimum36
Maximum5066596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:40.700945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile663.4
Q12673
median7351
Q322025
95-th percentile127957.8
Maximum5066596
Range5066560
Interquartile range (IQR)19352

Descriptive statistics

Standard deviation148374.29
Coefficient of variation (CV)4.0964775
Kurtosis324.9559
Mean36219.97
Median Absolute Deviation (MAD)5845
Skewness14.693201
Sum4.8987509 × 108
Variance2.201493 × 1010
MonotonicityNot monotonic
2025-08-02T14:13:40.849229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1295 7
 
0.1%
1748 6
 
< 0.1%
668 6
 
< 0.1%
2302 6
 
< 0.1%
789 6
 
< 0.1%
1332 6
 
< 0.1%
409 5
 
< 0.1%
2989 5
 
< 0.1%
721 5
 
< 0.1%
814 5
 
< 0.1%
Other values (10532) 13468
99.6%
ValueCountFrequency (%)
36 1
< 0.1%
51 1
< 0.1%
59 1
< 0.1%
67 1
< 0.1%
70 2
< 0.1%
73 1
< 0.1%
79 1
< 0.1%
80 2
< 0.1%
82 1
< 0.1%
83 1
< 0.1%
ValueCountFrequency (%)
5066596 1
< 0.1%
4972886 1
< 0.1%
3992661 1
< 0.1%
3402363 1
< 0.1%
2852789 1
< 0.1%
2564656 1
< 0.1%
2277881 1
< 0.1%
2239951 1
< 0.1%
2228361 1
< 0.1%
2166748 1
< 0.1%

avg_rating
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9191719
Minimum2.4
Maximum4.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size105.8 KiB
2025-08-02T14:13:40.970665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.4
5-th percentile3.4
Q13.7
median3.9
Q34.1
95-th percentile4.3
Maximum4.8
Range2.4
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.27822199
Coefficient of variation (CV)0.070989995
Kurtosis0.63179918
Mean3.9191719
Median Absolute Deviation (MAD)0.2
Skewness-0.45102299
Sum53006.8
Variance0.077407477
MonotonicityNot monotonic
2025-08-02T14:13:41.076754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3.9 1972
14.6%
4 1854
13.7%
4.1 1764
13.0%
3.8 1731
12.8%
3.7 1348
10.0%
4.2 1335
9.9%
4.3 858
6.3%
3.6 854
6.3%
3.5 488
 
3.6%
4.4 367
 
2.7%
Other values (15) 954
7.1%
ValueCountFrequency (%)
2.4 2
 
< 0.1%
2.5 3
 
< 0.1%
2.6 2
 
< 0.1%
2.7 1
 
< 0.1%
2.8 7
 
0.1%
2.9 22
 
0.2%
3 27
 
0.2%
3.1 56
 
0.4%
3.2 89
0.7%
3.3 191
1.4%
ValueCountFrequency (%)
4.8 3
 
< 0.1%
4.7 5
 
< 0.1%
4.6 45
 
0.3%
4.5 170
 
1.3%
4.4 367
 
2.7%
4.3 858
6.3%
4.2 1335
9.9%
4.1 1764
13.0%
4 1854
13.7%
3.9 1972
14.6%

similar_books
Text

Missing 

Distinct10613
Distinct (%)96.4%
Missing2515
Missing (%)18.6%
Memory size1.2 MiB
2025-08-02T14:13:41.412946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length178
Median length158
Mean length52.979564
Min length4

Characters and Unicode

Total characters583305
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10320 ?
Unique (%)93.7%

Sample

1st row341789
2nd row2037794, 2667475, 93582
3rd row1234050, 25125386, 25576, 39678, 2501288, 1220077, 21396582
4th row21856179
5th row3303291, 2643796, 859342, 15868401, 2060095, 7048306, 527677
ValueCountFrequency (%)
48682039 100
 
0.2%
45046034 77
 
0.1%
15064476 73
 
0.1%
17012687 65
 
0.1%
46757540 62
 
0.1%
47512648 60
 
0.1%
13380314 53
 
0.1%
18157137 53
 
0.1%
43242921 48
 
0.1%
41396000 48
 
0.1%
Other values (12105) 61650
99.0%
2025-08-02T14:13:41.934059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 65664
11.3%
4 58496
10.0%
2 57652
9.9%
, 51279
8.8%
51279
8.8%
5 45933
7.9%
3 44729
7.7%
6 44671
7.7%
8 42137
7.2%
9 41468
7.1%
Other values (2) 79997
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 583305
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 65664
11.3%
4 58496
10.0%
2 57652
9.9%
, 51279
8.8%
51279
8.8%
5 45933
7.9%
3 44729
7.7%
6 44671
7.7%
8 42137
7.2%
9 41468
7.1%
Other values (2) 79997
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 583305
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 65664
11.3%
4 58496
10.0%
2 57652
9.9%
, 51279
8.8%
51279
8.8%
5 45933
7.9%
3 44729
7.7%
6 44671
7.7%
8 42137
7.2%
9 41468
7.1%
Other values (2) 79997
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 583305
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 65664
11.3%
4 58496
10.0%
2 57652
9.9%
, 51279
8.8%
51279
8.8%
5 45933
7.9%
3 44729
7.7%
6 44671
7.7%
8 42137
7.2%
9 41468
7.1%
Other values (2) 79997
13.7%

Interactions

2025-08-02T14:13:29.808039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-08-02T14:13:10.752427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-08-02T14:13:14.002694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:15.438153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:17.169930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:18.767464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:20.317507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:22.660889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:24.681470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:26.210845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:28.005892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:29.492535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:31.027326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:10.918617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:12.429193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:14.111830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:15.538358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:17.280517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:18.887919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:20.427235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:22.849568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:24.801430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:26.306116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:28.106252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:29.596808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:31.131221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:11.063691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:12.553762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:14.229422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:15.655198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:17.387652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:19.003371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:20.541751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:23.048149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:24.920919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:26.412536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:28.231998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-02T14:13:29.704890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-08-02T14:13:42.047867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
1_star_ratings2_star_ratings3_star_ratings4_star_ratings5_star_ratingsavg_ratingisbn13num_pagesoriginal_publication_yearratings_countreviews_counttext_reviews_countwork_id
1_star_ratings1.0000.9680.9080.8420.796-0.069-0.2340.169-0.3720.8680.8850.851-0.370
2_star_ratings0.9681.0000.9680.9000.834-0.057-0.2660.154-0.4160.9170.9130.872-0.412
3_star_ratings0.9080.9681.0000.9710.9120.100-0.2730.164-0.4400.9750.9420.886-0.433
4_star_ratings0.8420.9000.9711.0000.9720.298-0.2420.205-0.4000.9950.9520.896-0.392
5_star_ratings0.7960.8340.9120.9721.0000.453-0.2090.212-0.3900.9780.9280.850-0.383
avg_rating-0.069-0.0570.1000.2980.4531.0000.0560.156-0.0160.2890.2160.159-0.012
isbn13-0.234-0.266-0.273-0.242-0.2090.0561.000-0.1830.211-0.242-0.244-0.2090.234
num_pages0.1690.1540.1640.2050.2120.156-0.1831.0000.0360.2000.2420.223-0.030
original_publication_year-0.372-0.416-0.440-0.400-0.390-0.0160.2110.0361.000-0.411-0.283-0.1520.937
ratings_count0.8680.9170.9750.9950.9780.289-0.2420.200-0.4111.0000.9590.896-0.403
reviews_count0.8850.9130.9420.9520.9280.216-0.2440.242-0.2830.9591.0000.933-0.290
text_reviews_count0.8510.8720.8860.8960.8500.159-0.2090.223-0.1520.8960.9331.000-0.159
work_id-0.370-0.412-0.433-0.392-0.383-0.0120.234-0.0300.937-0.403-0.290-0.1591.000

Missing values

2025-08-02T14:13:31.330685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-08-02T14:13:31.546968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-08-02T14:13:31.804874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

work_idisbnisbn13original_titleauthororiginal_publication_yearnum_pagesdescriptiongenresimage_urlreviews_counttext_reviews_count5_star_ratings4_star_ratings3_star_ratings2_star_ratings1_star_ratingsratings_countavg_ratingsimilar_books
0291913014165346019.781417e+12NocturnesJohn Connolly2004.0NaNNaNfiction, fantasy, paranormal, mystery, thriller, crime, young-adulthttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png88203381118160110291905839963.9NaN
152087333NaNNaNDraw PlayTia Lewis2016.0NaNJake:\nI can't believe my coach assigned me a tutor. I'm all that on the field and between the sheets -- who cares about my stupid grades?\nBut Claire doesn't treat me like I'm dumb. When we're not busy fighting, she actually encourages me. And with those sexy curves of hers, I know just how to thank her.\nClaire:\nI hate football players, but I need the money. Jake is just as cocky and arrogant as the worst of them ... but his touch sets me on fire.\nI have to believe he's different, that he won't use me and break my heart. Because I can't stop wanting him. I just hope I survive the ride.romance, fictionhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png248220420435327477299373.7NaN
2164958314165055209.781417e+12Citizen of the GalaxyRobert A. Heinlein1957.0NaNIn a distant galaxy, the atrocity of slavery was alive and well, and young Thorby was just another orphaned boy sold at auction. But his new owner, Baslim, is not the disabled beggar he appears to be: adopting Thorby as his son, he fights relentlessly as an abolitionist spy. When the authorities close in on Baslim, Thorby must ride with the Free Traders a league of merchant princes throughout the many worlds of a hostile galaxy, finding the courage to live by his wits and fight his way from society's lowest rung. But Thorby's destiny will be forever changed when he discovers the truth about his own identity...fiction, young-adult, fantasy, paranormal, childrenhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png1650644735394351286344453112504.0NaN
368829900605418309.780061e+12CongoMichael Crichton1980.0NaNDeep in the African rain forest, near the legendary ruins of the Lost City of Zinj, an expedition of eight American geologists is mysteriously and brutally killed in a matter of minutes.\nTen thousand miles away, Karen Ross, the Congo Project Supervisor, watches a gruesome video transmission of the aftermath: a camp destroyed, tents crushed and torn, equipment scattered in the mud alongside dead bodies -- all motionless except for one moving image -- a grainy, dark, man-shaped blur.\nIn San Francisco, primatologist Peter Elliot works with Amy, a gorilla with an extraordinary vocabulary of 620 "signs," the most ever learned by a primate, and she likes to fingerpaint. But recently, her behavior has been erratic and her drawings match, with stunning accuracy, the brittle pages of a Portuguese print dating back to 1642 . . . a drawing of an ancient lost city. A new expedition -- along with Amy -- is sent into the Congo where they enter a secret world, and the only way out may be through a horrifying death . . .fiction, mystery, thriller, crime, fantasy, paranormalhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png17091616332508145775485051400129261362883.6NaN
4346426404515288249.780452e+12Anne of Green GablesL.M. Montgomery1908.0NaNEveryone's favorite redhead, the spunky Anne Shirley, begins her adventures at Green Gables, a farm outside Avonlea, Prince Edward Island. When the freckled girl realizes that the elderly Cuthberts wanted to adopt a boy instead, she begins to try to win them and, consequently, the reader, over.fiction, young-adult, children, history, historical fiction, biography, romancehttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png74339214586272952161856815781993390995454184.2NaN
54560004252101389.780425e+12High StakesErin McCarthy2006.0NaNFrom the USA Today bestselling author, a vampire-meets-girl story set in the city that never sleeps-except during daylight.\nHe's a bloodsucking freak of nature. But, unlike other politicians, Ethan Carrick is actually a nice guy. Not to mention a very hot, wealthy, casino-owning vampire. It's an election year for vampires, which means he'll first have to escape his opponent's hit men. Then he'll have to find a suitable First Lady, preferably here in Vegas.\nBrittany Baldizzi fits the bill. She's smart, pretty- and sweeter than a glass of diabetic O-Negative. But her protective sister Alexis steps in with a message for Ethan: Bite me. It's then that he realizes it's the sexy, no-nonsense Alexis who raises his stake. And as much as she denies it, Alexis wouldn't mind a romp in the coffin with him. But can a mere mortal, even one who risks her life for him, make a centuries-old, womanizing vampire feel something entirely new?fantasy, paranormal, romance, fiction, mystery, thriller, crimehttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png1211927316492116190658017264233.7NaN
623384315955405479.781596e+12When Crickets CryCharles Martin2006.0NaNA man with a painful past. A child with a doubtful future. And a shared journey toward healing for both their hearts.\nIt begins on the shaded town square in a sleepy Southern town. A spirited seven-year-old has a brisk business at her lemonade stand. But the little girl's pretty yellow dress can't quite hide the ugly scar on her chest.\nHer latest customer, a bearded stranger, drains his cup and heads to his car, his mind on a boat he's restoring at a nearby lake. The stranger understands more about the scar than he wants to admit. And the beat-up bread truck careening around the corner with its radio blaring is about to change the trajectory of both their lives.\nBefore it's over, they'll both know there are painful reasons why crickets cry . . . and that miracles lurk around unexpected corners.fiction, romancehttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png217261767559940341677394143118474.2NaN
73486007653163159.780765e+12The Ice DragonGeorge R.R. Martin1980.0NaNThe ice dragon was a creature of legend and fear, for no man had ever tamed one. When it flew overhead, it left in its wake desolate cold and frozen land. But Adara was not afraid. For Adara was a winter child, born during the worst freeze that anyone, even the Old Ones, could remember. Adara could not remember the first time she had seen the ice dragon. It seemed that it had always been in her life, glimpsed from afar as she played in the frigid snow long after the other children had fled the cold. In her fourth year she touched it, and in her fifth year she rode upon its broad, chilled back for the first time. Then, in her seventh year, on a calm summer day, fiery dragons from the North swooped down upon the peaceful farm that was Adaras home. And only a winter child -- and the ice dragon who loved her -- could save her world from utter destruction. The Ice Dragon marks the highly anticipated childrens book debut of George R.R. Martin, the award-winning author of the best-selling series A Song of Ice and Fire and is set in the same world. Illustrated with lush, exquisitely detailed pencil drawings by acclaimed artist Yvonne Gilbert, The Ice Dragon is an unforgettable tale of courage, love, and sacrifice by one of the most honored fantasists of all time.fantasy, paranormal, children, young-adult, fiction, comics, graphichttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png202481561247843433207607143107783.8NaN
897933314165099099.781417e+12On a Highland ShoreKathleen Givens2006.0NaNFrom acclaimed historical novelist Kathleen Givens comes a magnificently conceived, intricately detailed novel that brings to vivid life the tumult, adventure, and passion of thirteenth-century Scotland, when Norse invaders laid claim to the land and its people--and an explosive clash of cultures, politics, and personal pride changed the world forever.\nOn Scotland's western shore, the village of Somerstrath prepares for the joyous wedding celebration of Margaret MacDonald, the laird's daughter. But a dark storm of bloodshed and betrayal is closing in, as a merciless band of Vikings threatens the Highlands.\nMargaret is determined to hold the MacDonald clan together and to locate her abducted younger brother. But can she trust the noblemen from King Alexander's court, who insist that only by adhering to a betrothal conceived for political gain will she find safety? Or should she put her trust in an imposing half-Irish, half-Norse warrior?\nGannon MacMagnus alone offers her hope of reuniting her family and vanquishing the barbarous Norsemen who would continue to rob her people of their God-given right to determine their own destinies. In whom should Margaret entrust the fate of the rugged, magnificent land she calls home?fiction, history, historical fiction, biography, romance, fantasy, paranormalhttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png106811947119807211986726773.8NaN
970979308423292189.780842e+12Tribulation Force: The Continuing Drama of Those Left BehindTim LaHaye1996.0NaNIn one cataclysmic moment, millions around the globe disappear.\nThose left behind face war, famine, plagues, and natural disasters so devastating that only one in four people will survive. Odds are even worse for enemies of the Antichrist and his new world order.\nRayford Steele, Buck Williams, Bruce Barnes, and Chloe Steele band together to form the Tribulation Force. Their task is clear, and their goal is nothing less than to stand and fight the enemies of God during the seven most chaotic years the planet will ever see.fiction, fantasy, paranormal, mystery, thriller, crime, romancehttps://s.gr-assets.com/assets/nophoto/book/111x148-bcc042a9c91a29c1d680899eff700a03.png45968835119481072470242021913326303.9NaN
work_idisbnisbn13original_titleauthororiginal_publication_yearnum_pagesdescriptiongenresimage_urlreviews_counttext_reviews_count5_star_ratings4_star_ratings3_star_ratings2_star_ratings1_star_ratingsratings_countavg_ratingsimilar_books
1351555248711NaNNaNMy Sexy ProfessorJuliette Jones2017.075.0Ivy Quinn has a problem: she can't stop fantasizing about her sexy professor. Economics class has become pure torture, until she makes a pact with herself: she's going to seduce him. But can she get this sexy buttoned-up beast to unleash his wild side?\nColton Harrison also has a problem. He's sporting a perpetual hard-on for the ridiculously hot student who sits in the front row of his freshman economics class. This is not only becoming obvious, it's also jeopardizing his job. But when Ivy comes to his office to get some extra help, there's no way in hell he can resist taking what's his.\nMY SEXY PROFESSOR is a super-sexy quickie guaranteed to get you an A ... er, I mean O :)romance, fictionhttps://images.gr-assets.com/books/1487021151m/34202968.jpg5546739676430132133.4NaN
1351654660596NaNNaNDarkest Hour Before DawnCharlie Cochet2017.0224.0THIRDS Team Leader Sebastian Hobbs and Chief Medical Examiner Hudson Colbourn are as much in love now as they were nearly seven years ago when a tragic event on the job destroyed their relationship. The two drift together only to be pulled apart time and time again. When Hudson draws the interest of dangerous enemies, both within and outside the organization, Seb wants nothing more than to protect the man who still means everything to him.\nAs life and death events, an uncertain future, and startling truths draw Hudson and Seb to each other yet again, they must make a choice: trust their love and take strength from what they share, or lose what matters most for good this time.fantasy, paranormal, romance, mystery, thriller, crime, fictionhttps://images.gr-assets.com/books/1487037731m/33780462.jpg232225454351019735712924.2NaN
1351753979944NaNNaNThe Duchess DealTessa Dare2017.0389.0When girl meets Duke, their marriage breaks all the rules...\nSince his return from war, the Duke of Ashbury's to-do list has been short and anything but sweet: brooding, glowering, menacing London ne'er-do-wells by night. Now there's a new item on the list. He needs an heir--which means he needs a wife. When Emma Gladstone, a vicar's daughter turned seamstress, appears in his library wearing a wedding gown, he decides on the spot that she'll do.\nHis terms are simple:\n- They will be husband and wife by night only.\n- No lights, no kissing.\n- No questions about his battle scars.\n- Last, and most importantly... Once she's pregnant with his heir, they need never share a bed again.\nBut Emma is no pushover. She has a few rules of her own:\n- They will have dinner together every evening.\n- With conversation.\n- And unlimited teasing.\n- Last, and most importantly... Once she's seen the man beneath the scars, he can't stop her from falling in love...romance, history, historical fiction, biography, fictionhttps://images.gr-assets.com/books/1490030736m/33259027.jpg130061015207920468631966252464.1NaN
1351857438069NaNNaNHow to Save a LifeEli Easton2017.0238.0Rav Miller looked into the terrified, intelligent eyes of the chocolate Labrador on death row, and knew he'd do anything to save him. When the dog, Sammy, escapes and heads to Mad Creek, Rav follows. Mad Creek. The town had become legendary in Rav's mind after he'd met that bizarre group last year. Rav dismissed his crazy suspicions back then, but when he arrives in Mad Creek, he knows it's true. Dog shifters exist, and apparently they all live in the California mountains. It's enough to blow a bad boy's mind.\nSammy has something in common with Rav--neither one of them trusts people. After Sammy's abuse as a dog, he particularly dislikes tough-looking men like Rav. But when Sammy gets a chance to work with rescued dogs at the new Mad Creek shelter, his deep compulsion to help others overcomes his fear. Rav and Sammy bond over saving strays. If they can each find the courage to let someone else in, they might find their way to love.\nSheriff Lance Beaufort doesn't like humans moving into Mad Creek, especially not the tattooed and defiant Rav. When Rav starts a rescue shelter, the town thinks he's wonderful! But Lance isn't fooled. He doesn't buy Rav's innocent act for one second. How much does Rav know about the quickened? What is his game? And why did he have to show up now, when Lance and the other town leaders are overwhelmed by all the new quickened pouring in?\nRav knows how to save a life. But can he save an entire town? Can he rescue Mad Creek?fantasy, paranormal, romancehttps://images.gr-assets.com/books/1501835023m/35910868.jpg13861992752911691637544.1NaN
1351951832868NaNNaNAgents of DreamlandCaitlin R. Kiernan2017.0112.0A government special agent known only as the Signalman gets off a train on a stunningly hot morning in Winslow, Arizona. Later that day he meets a woman in a diner to exchange information about an event that happened a week earlier for which neither has an explanation, but which haunts the Signalman.\nIn a ranch house near the shore of the Salton Sea a cult leader gathers up the weak and susceptible--the Children of the Next Level--and offers them something to believe in and a chance for transcendence. The future is coming and they will help to usher it in.\nA day after the events at the ranch house which disturbed the Signalman so deeply that he and his government sought out help from 'other' sources, Johns Hopkins Applied Physics Laboratory abruptly loses contact with NASA's interplanetary probe New Horizons. Something out beyond the orbit of Pluto has made contact.\nAnd a woman floating outside of time looks to the future and the past for answers to what can save humanity.fiction, fantasy, paranormal, mystery, thriller, crimehttps://images.gr-assets.com/books/1474734054m/31189177.jpg4986219242434277732310493.8NaN
1352054014359NaNNaNThe Billionaire Beast: A Billionaire Romance (The Billionaire Fairy Tales)Jackie Ashenden2017.0212.0Dark, tortured, and intimidating, these dominant billionaires will steal their innocent heroines' breath away. Overwhelmed by their desire to control their world, they push their heroines to explore their deepest desires. But even the most unworldly of heroines can unlock these billionaires' secrets.\nNero de Santis: Damaged. Bastard. Beast. \nNero hasn't left his house in ten years--he demands the world come to him, and the world is only too happy to bend to the strong-willed billionaire. Ruthless, cold, and selfish, Nero wants for nothing and takes care of no one but himself. His last handful of assistants have left his house in tears, but the prim redhead applying for the job looks up to the task. Nero has spent his life shut within the walls he built, with no care to have more than a window to the outside world. But the fiery passion he senses beneath his reserved assistant's exterior makes him want to break down the barriers he lives behind, and unleash the beast within.\nPhoebe Taylor: Uptight. Misunderstood. Engaged. \nPhoebe needs the obscene amount of money that comes with being Nero's personal assistant for one thing, and one thing only--to pay for the mounting hospital costs that her fiancee's two-year coma continues to incur. She's heard rumors that the de Santis beast is a force that cannot be tamed--but even she isn't prepared to handle the smoldering intensity simmering beneath his hard shell of feral dominance. Nero is hiding something, something he is fighting with every step he takes. Yet he can't help but stake his claim on this woman who has shaken up his life, and Phoebe can't believe this animal of a man is the one person to ever look into her eyes and see her soul. Nero wants to keep her. He wants to devour her. And Phoebe just might let him.romance, fictionhttps://images.gr-assets.com/books/1483314230m/33286936.jpg713138102123723263353.8NaN
1352155464075NaNNaNForeverMonica Murphy2017.0221.0She's all I could ever want...\nI have a reputation around school. Cold. Untouchable. Unfeeling. Only one girl could ever make me want to change and that's Amanda Winters. Too bad I broke her heart and drove her away.\nSo to get through the rest of my days in high school, I tell myself I need to focus on more important things. Like taking our football team to championships. Get accepted to the college of my choice. And finish my senior year without wanting to run away from my problems.\nBut your problems chase after you no matter where you go. And it's a lot harder when you fight them alone. The longer I go without Amanda, the more I miss her. Her smile. Her laughter. The things she said. How she looked at me like I was the only person who mattered. The way she made me feel...\nWhy can't I have everything, including the girl? I'm determined to make things right. And make Amanda mine...\nForever.romance, young-adulthttps://images.gr-assets.com/books/1490712510m/33957722.jpg188112917018412825115183.9NaN
1352254275347NaNNaNMost Valuable PlayboyLauren Blakely2017.0300.0Hands down, my favorite thing in the world is to score. Touchdowns.\nDon't let the fact that I'm the leading pick in the Most Valuable Playboy charity auction fool you. These days, I'm only a player on the field. I've kept my pants zipped all season long--and it has been long--because nothing's more important than leading my team to victory every week. Except maybe escaping from the team owner's recently-widowed and handsy-as-hell sister who's dead set on winning more than a date with me.\nEnter Violet and a well-placed Hail Mary.\nShe's my best friend's sister with a smile as sweet as cherry pie and a mind that runs quicker than the 40-yard-dash. After Violet saves the day with the highest bid, I don't even give her a two-minute warning before I kiss her in front of the whole crowd and then announce that she's my girlfriend. Which would be fine except my agent tells me we've got to keep up the act while he's negotiating my contract.\nViolet takes one for the team and pretends to be mine, but our boyfriend-girlfriend scrimmage quickly turns into a full contact sport, and I want it to go into overtime. The problem is--I've been riding the bench for years.\nHow can a guy like me, who finally has a chance to prove his worth on the field, convince the girl she's most valuable to his heart?\nMOST VALUABLE PLAYBOY is a brand new standalone sports romance written in the guy's POV!romance, fictionhttps://images.gr-assets.com/books/1510251456m/33515066.jpg1107345311331109451883028114.1NaN
1352356412634NaNNaNThe Bet (Player Series)Elizabeth Hayley2017.0274.0Jace "the Jet" Benning is a legend on the football field. And off. He has the arm, the charm, and the reputation of being the hottest player in the league.\nToo bad Dr. Alessandra Mastrazacoma is not impressed.\nWith a busy schedule and a bruised heart, Alessandra doesn't have time to date, but when she is lured into making a friendly bet with her best friend, she finds herself agreeing to go out with the next guy that asks...and to give him three shots, three dates, before pulling the plug.\nJace also has a friendly wager with his friends going, and it involves making sure the slightly klutzy, but very pretty, doctor will be his date to the biggest night in sports. With two wagers and two hearts on the line, will Aly and Jace win or are they betting to lose?romance, fiction, young-adulthttps://images.gr-assets.com/books/1494364595m/35105549.jpg334642442261051073.7NaN
1352451402505NaNNaNDanced CloseAnnabeth Albert2017.0132.0Portland, Oregon, is one of the hottest cities in America. Just ask all the hard-working men sweating it up behind the counters of the restaurants, boutiques, and cafes all over town ... \nNewly clean and sober, Todd's taken a shine to his job at Portland's most talked about bakery. It's not just the delicious desserts they sell, but the tasty treats who keep walking through the door. That certainly includes Kendall Rose, a wedding planner with eyes the color of brown sugar and skin to match. Todd doesn't try to hide his attraction to Kendall's elegant confidence and unique style, even as he worries about exposing the secrets of his past.\nFor Kendall, the attention is just part of the anything-goes Portland he's grown to love. But he's still looking for that special someone who will embrace all of him--including his gender fluidity. So he takes a chance and asks Todd to be his partner in a dance class leading to a fundraiser. When the music starts and he takes Todd in his arms, Kendall is shocked at how good it feels. Turns out taking the lead for once isn't a mistake. In fact, it might be time to take the next step and follow his heart ...romance, fictionhttps://images.gr-assets.com/books/1474433250m/30814007.jpg9351311072071332534753.8NaN